OBJECTIVE: Evaluate the relationship between the chemical composition of C. nutans and its anti-inflammatory properties using nuclear magnetic resonance (NMR) metabolomics approach.
METHODOLOGY: The anti-inflammatory effect of C. nutans air-dried leaves extracted using five different binary extraction solvent ratio and two extraction methods was determined based on their nitric oxide (NO) inhibition effect in lipopolysaccharide-interferon-gamma (LPS-IFN-γ) activated RAW 264.7 macrophages. The relationship between extract bioactivity and metabolite profiles and quantifications were established using 1 H-NMR metabolomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The possible metabolite biosynthesis pathway was constructed to further strengthen the findings.
RESULTS: Water and sonication prepared air-dried leaves possessed the highest NO inhibition activity (IC50 = 190.43 ± 12.26 μg/mL, P
METHODS AND FINDINGS: The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
CONCLUSIONS: These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
Method: A retrospective review case records of patients who had undergone external ventricular drainage (EVD) for suspected meningitic hydropcephalus in Hospital Sultanah Aminah Johor Bahru (HSAJB), Johor, Malaysia.
Results: Fifty-one cases were analysed. Mean age of patients was 37.27 years old, with 64.7% of them was male. Univariate analysis revealed that the main parameters to determine CSF sterility were CSF glucose (95% CI, 0.852, 10.290, P = 0.001), CSF protein (CI 95%, 0.722, 14.898, P < 0.001), CSF gram stain (95% CI, 16.437, 0.877, P < 0.001 ) and CSF appearance ( 0.611, 6.362, P = 0.012). Multivariate analysis had proven that gram stain was the main parameter in the CSF analysis (CI 95%, 16.437, 0.029, P = 0.016). No significant differences in CSF results were observed from EVD and lumbar puncture.
Conclusion: The most significant parameter in CSF to determine infection was gram stain.
METHODS: Patient data was obtained retrospectively through the Ministry of Health, Malaysia, from 2011 to 2016. Patients with incomplete data were excluded. A total of 2044 clinical P. vivax malaria cases treated with primaquine were included. Data collected were patient, disease, and treatment characteristics. Two-thirds of the cases (n = 1362) were used to develop a clinical risk score, while the remaining third (n = 682) was used for validation.
RESULTS: Using multivariate analysis, age (p = 0.03), gametocyte sexual count (p = 0.04), indigenous transmission (p = 0.04), type of treatment (p = 0.12), and incomplete primaquine treatment (p = 0.14) were found to be predictors of recurrence after controlling for other confounding factors; these predictors were then used in developing the final model. The beta-coefficient values were used to develop a clinical scoring tool to predict possible recurrence. The total scores ranged between 0 and 8. A higher score indicated a higher risk for recurrence (odds ratio [OR]: 1.971; 95% confidence interval [CI]: 1.562-2.487; p ≤ 0.001). The area under the receiver operating characteristic (ROC) curve of the developed (n = 1362) and validated model (n = 682) was of good accuracy (ROC: 0.728, 95% CI: 0.670-0.785, p value
METHODS: Planned analysis of data was collected during an international 7-day cohort study of adults undergoing elective in-patient surgery. AKI was defined using Kidney Disease Improving Global Outcomes criteria. Patients missing preoperative creatinine data were excluded. We used multivariable logistic regression to examine the relationships among preoperative creatinine-based estimated glomerular filtration rate (eGFR), postoperative AKI, and hospital mortality, accounting for the effects of age, major comorbid diseases, and nature and severity of surgical intervention on outcomes. We similarly modeled preoperative associations of AKI. Data are presented as n (%) or odds ratios (ORs) with 95% confidence intervals.
RESULTS: A total of 36,357 patients were included, 743 (2.0%) of whom developed AKI with 73 (9.8%) deaths in hospital. AKI affected 73 of 196 (37.2%) of all patients who died. Mortality was strongly associated with the severity of AKI (stage 1: OR, 2.57 [1.3-5.0]; stage 2: OR, 8.6 [5.0-15.1]; stage 3: OR, 30.1 [18.5-49.0]). Low preoperative eGFR was strongly associated with AKI. However, in our model, lower eGFR was not associated with increasing mortality in patients who did not develop AKI. Conversely, in older patients, high preoperative eGFR (>90 mL·minute·1.73 m) was associated with an increasing risk of death, potentially reflecting poor muscle mass.
CONCLUSIONS: The occurrence and severity of AKI are strongly associated with risk of death after surgery. However, the relationship between preoperative renal function as assessed by serum creatinine-based eGFR and risk of death dependent on patient age and whether AKI develops postoperatively.